The vision of the Cluster of Excellence Integrative Computational Design and Construction for Architecture (EXC IntCDC) is to harness the full potential of digital technologies in order to rethink design, fabrication and construction based on integration and interdisciplinarity, with the goal of enabling game-changing innovation in the building sector as it can only occur through highly integrative fundamental research in an interdisciplinary, large-scale research undertaking.

The Cluster aims to lay the methodological foundations for a profound rethinking of the design and building process and related building systems by adopting an integrative computational approach based on interdisciplinary research encompassing architecture, structural engineering, building physics, engineering geodesy, manufacturing and system engineering, computer science and robotics, social sciences and humanities. We aim to bundle the internationally recognised competencies in these fields of the University of Stuttgart and the Max Planck Institute for Intelligent Systems to accomplish our research mission.

The Cluster’s Industry Consortium will ensure direct knowledge exchange, transfer and rapid impact. Taking into account the significant difference between the building industry and other industries, we will tackle the related key challenges of achieving a higher level of integration, performance and adaptability, and we will address the most important building typologies of multi-storey buildings, long-span buildings, and the densification of urban areas.

The Cluster’s broad methodological insights and interdisciplinary findings are expected to result in comprehensive approaches to harnessing digital technologies, which will help to address the ecological, economic and social challenges that current incremental approaches cannot solve.

We envision IntCDC to significantly shape the future of architecture and the building industry through a higher-level integration of computational design and engineering methods, effective cyber-physical (tightly interlinked computational and material) robotic construction processes and new forms of human-machine collaboration, efficient and sustainable next-generation building systems, and socio-cultural and ethical reflection. Thus, the Cluster will have significant impact on creating the conditions required for a liveable and sustainable future built environment, high-quality yet affordable architecture and a novel digital building culture.
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1 to 10 of 71 Results
Sep 29, 2022 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Müller, Christoph; Braun, Matthias; Weiskopf, Daniel; Schreiber, Falk, 2022, ""Research Data Curation in Visualization : Position Paper" (Data)", https://doi.org/10.18419/darus-3144, DaRUS, V1, UNF:6:yUhRXAoSoLD387EnHtthFg== [fileUNF]
Here, we make available the supplemental material regarding data collection from the publicaiton "Research Data Curation in Visualization : Position Paper". The dataset represents an aggregated collection of the data policies of selected publication venues in the areas of visuali...
Jun 30, 2022 - ABxM Framework for Agent-based Modeling and Simulation
Nguyen, Long; Schwinn, Tobias; Groenewolt, Abel; Maierhofer, Mathias; Zorn, Max Benjamin; Stieler, David; Siriwardena, Lasath; Kannenberg, Fabian; Menges, Achim, 2022, "ABxM.Core: The Core Libraries of the ABxM Framework", https://doi.org/10.18419/darus-2994, DaRUS, V1
The ABxM.Core consists of the agent core library ABxM.Core and an interoperability library for Rhino 6 and later versions. ABxM.Core implements the functionality specific to agent-based modelling and simulation. The core library can, in principle, be referenced from any applicati...
Mar 13, 2024 - EXC IntCDC Research Project 19 'Co-Design Methods for Developing Distributed Cooperative Multi-Robot Systems for Construction'
Leder, Samuel; Siriwardena, Lasath; Menges, Achim, 2024, "ABxM.DistributedRobotics.RADr: Agent-based Design and Control of multiple Roaming Autonomous Distributed robots (RADr)", https://doi.org/10.18419/darus-4058, DaRUS, V1
ABxM.DistributedRobotics.RADr is an add-on to ABxM.Core for agent-based design and control of multiple Roaming Autonomous Distributed robots (RADr) that assemble hexagonal digital materials. The add-on contains various agent system constructs and utilities for simulation of the s...
Dec 11, 2023 - ABxM Framework for Agent-based Modeling and Simulation
Schwinn, Tobias; Groenewolt, Abel; Nguyen, Long; Siriwardena, Lasath; Alvarez, Martín; Reiner, Alexander; Zorn, Max Benjamin; Menges, Achim, 2023, "ABxM.PlateStructures: Agent-based Architectural Design of Plate Structures", https://doi.org/10.18419/darus-3438, DaRUS, V3
ABxM.PlateStructures is an add-on to ABxM.Core for agent-based design and development of plate structures, such as segmented timber shells. The add-on contains various agent system constructs and utilities for plate structure design and is intended to be used within Rhino/Grassho...
Mar 3, 2023 - EXC IntCDC Research Project 20 'Knowledge Representation for Multi-Disciplinary Co-Design'
Elshani, Diellza; Lombardi, Alessio; Hernández, Daniel; Staab, Steffen; Fisher, Al; Wortmann, Thomas, 2023, "BHoM to bhOWL converter", https://doi.org/10.18419/darus-3364, DaRUS, V1
The dataset is the release version v2.0.0 of the BHoM to bhOWL converter, which helps convert BHoM data to a knowledge graph in any software BHoM supports. BHoM (The Buildings and Habitats object Model) is collaborative framework that runs within several AEC design software, whic...
Feb 21, 2024 - Analytic Computing
Asma, Zubaria; Hernández, Daniel; Galárraga, Luis; Flouris, Giorgos; Fundulaki, Irini; Hose, Katja, 2024, "Code and benchmark for NPCS, a Native Provenance Computation for SPARQL", https://doi.org/10.18419/darus-3973, DaRUS, V1
Code for the implementation and benchmark of NPCS, a Native Provenance Computation for SPARQL. The code in this dataset includes the implementation of the NPCS system, which is a middleware for SPARQL endpoints that rewrites queries to queries that annotate answers with provenanc...
Feb 16, 2024 - Analytic Computing
Seifer, Philipp; Hernández, Daniel; Lämmel, Ralf; Staab, Steffen, 2024, "Code for From Shapes to Shapes", https://doi.org/10.18419/darus-3977, DaRUS, V1
This dataset contains the implementation code for an algorithm to infer SHACL shapes that the graph returned by an SPARQL CONSTRUCT query must satisfy if the input satisfies a given set of SHACL shapes. This dataset also includes an evaluation for the algorithm. The algorithm imp...
Feb 27, 2024 - EXC IntCDC Research Project 29 'COLife: More-Than-Human Perspective to Codesign'
Davidova, Marie; Teye, Martha Teiko; Fischer, Leonie Katharina; Valverde Rojas, María Claudia; Behnam, Hananeh; Guimaraez di Stasi, Mariah; He, Mengxi; Hildebrandt, Harrison; Chau, Wai Man; Pittiglio, Alexandra; Asa, Pelin; Kuo, Chien Chun; Blagojevic, Emilija; Hillebrecht, Robin; Hillemanns, Theresa; Schaal, Maren; Spielvogel, Marcel; Sweeting, Ben; Goodbun, John; Perera, Dulmini, 2024, "COLife_00 - Gigamap and Fabrication Data", https://doi.org/10.18419/darus-3981, DaRUS, V1
The dataset covers codesign gigamapping data and the 3d parametric models from Rhino 3d of a set of responsive wood insect hotels with pollinator's gardens from the year 2022/23. The first set of gigamaps are for the first intervention POL-AI1, the second for its iteration POL-AI...
Feb 27, 2024 - EXC IntCDC Research Project 29 'COLife: More-Than-Human Perspective to Codesign'
Davidova, Marie; Valverde Rojas, María Claudia; Behnam, Hananeh; Fischer, Leonie Katharina; Fadini, Thomas; Haueise, Jannis; Hauke, Adriana; Florescu, Matei; Ferrari, Valentina; Ros, Ana Patricia; Vujovic, Nadja; Knutelsky, Samuel; Wosiak, Olga; Candìa, Marcelo, 2024, "COLife_01 - Gigamap and DIY Files", https://doi.org/10.18419/darus-3983, DaRUS, V1
The data cover codesigned gigamap and parametric and analogue DIY files of BioDiveIn more-than-human intervention. The gigamap was a product of digital participation in the Miro platform, updated by analogue workshops with stakeholders in feedback loops. The data were produced in...
Feb 27, 2024 - EXC IntCDC Research Project 29 'COLife: More-Than-Human Perspective to Codesign'
Davidova, Marie; Behnam, Hananeh; Valverde Rojas, María Claudia; Guerriero, Cristina; Yeh, Hsuan; Huang, Jianing; Köse, Mahir, 2024, "COLife_02 - Gigamap and Game Design", https://doi.org/10.18419/darus-3985, DaRUS, V1
The dataset covers a gigamapping of game design and execution of the game GoCOLife that introduces a more-than-human perspective to the players. The data were produced as part of a studio course 'COLife: More-than-Human Perspective to CoDesign' in the summer semester 2024.
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